Pairwise Perturbative Ansatz for Quantum Process Tomography Part 2: Experiment

Luke C. G. Govia, Guilhem J. Ribeill, Matthew Ware +1 more

L. C. G. Govia, G. J. Ribeill, Diego Ristè +2 more

Quantum process tomography has become increasingly critical as the need grows for robust verification and validation of candidate quantum processors, since it plays a key role in both performance assessment and debugging. However, as these processors grow in size, standard process tomography becomes an almost impossible task. Here, we present an approach for efficient quantum process tomography that uses a physically motivated ansatz for an unknown quantum process. Our ansatz bootstraps to an effective description for an unknown process on a multi-qubit processor from pairwise two-qubit tomographic data. Further, our approach can inherit insensitivity to system preparation and measurement error from the two-qubit tomography scheme. We benchmark our approach using numerical simulation of noisy three-qubit gates, and show that it produces highly accurate characterizations of quantum processes. Further, we demonstrate our approach experimentally on a superconducting quantum processor, building three-qubit gate reconstructions from two-qubit tomographic data.

Yu-Xiang Zhang, Xuanmin Zhu, Shengjun Wu +1 more

Luke C. G. Govia, Guilhem J. Ribeill, Diego Ristè +2 more

Abstract Quantum process tomography has become increasingly critical as the need grows for robust verification and validation of candidate quantum processors, since it plays a key role in both performance assessment and debugging. However, as these processors grow in size, standard process tomography becomes an almost impossible task. Here, we present an approach for efficient quantum process tomography that uses a physically motivated ansatz for an unknown quantum process. Our ansatz bootstraps to an effective description for an unknown process on a multi-qubit processor from pairwise two-qubit tomographic data. Further, our approach can inherit insensitivity to system preparation and measurement error from the two-qubit tomography scheme. We benchmark our approach using numerical simulation of noisy three-qubit gates, and show that it produces highly accurate characterizations of quantum processes. Further, we demonstrate our approach experimentally on a superconducting quantum processor, building three-qubit gate reconstructions from two-qubit tomographic data.

Yi Hu, Congcong Zheng, Xiaojun Wang +3 more

Anton Nykänen

A methodology to explore quantum entanglement phenomena on near-term quantum computers is presented. The method combines two prominent Noisy Intermediate-Scale Quantum (NISQ) algorithms, the variational quantum eigensolver (VQE) and pairwise tomography, to extract pairwise quantum properties from quantum many-body systems. VQE prepares a parametrized quantum circuit and optimizes it to represent the ground state of the system under study. Pairwise tomography provides an exponential decrease in the required measurements to construct two-qubit reduced density matrices. Two pairwise quantities, mutual information and concurrence, are used to construct complex network representations of the system. Then, network properties can be used to analyze the entanglement structures. Three quantum spin chains are explored: the Ising model, the spin-1/2 XX model and the XXZ model. The methodology is benchmarked with known results and new results for the XXZ model are presented. Applications for the study of fundamental physics are explored. More specifically, emergent space from quantum entanglement is studied. Mutual information between parts of a redundancy-constrained system is used to define a metric that is then embedded into a smooth manifold embedded in Rᴰ. Effects of entanglement perturbations on the geometry of the embedding are studied.